scholarly journals Application of Individualized Speed Zones to Quantify External Training Load in Professional Soccer

2020 ◽  
Vol 72 (1) ◽  
pp. 279-289 ◽  
Author(s):  
Vincenzo Rago ◽  
João Brito ◽  
Pedro Figueiredo ◽  
Peter Krustrup ◽  
António Rebelo
Keyword(s):  
High Speed ◽  
Training Load ◽  
Monitoring Methods ◽  
Absolute Level ◽  
Professional Soccer ◽  
Maximal Aerobic Speed ◽  
Maximal Speed ◽  
External Training ◽  
Soccer Team ◽  
Sprinting Speed

AbstractThis study aimed to examine the interchangeability of two external training load (ETL) monitoring methods: arbitrary vs. individualized speed zones. Thirteen male outfield players from a professional soccer team were monitored during training sessions using 10-Hz GPS units over an 8-week competitive period (n = 302 observations). Low-speed activities (LSA), moderate-speed running (MSR), high-speed running (HSR) and sprinting were defined using arbitrary speed zones as <14.4, 14.4–19.8, 19.8–25.1 and ≥25.2 km·h-1, and using individualized speed zones based on a combination of maximal aerobic speed (MAS, derived from the Yo-yo Intermittent recovery test level 1), maximal sprinting speed (MSS, derived from the maximal speed reached during training) and anaerobic speed reserve (ASR) as <80% MAS, 80–100% MAS, 100% MAS or 29% ASR and ≥30% ASR. Distance covered in both arbitrary and individualized methods was almost certainly correlated in all speed zones (p < 0.01; r = 0.67-0.78). However, significant differences between methods were observed in all speed zones (p < 0.01). LSA was almost certainly higher when using the arbitrary method than when using the individualized method (p < 0.01; ES = 5.47 [5.18; 5.76], respectively). Conversely, MSR, HSR and sprinting speed were higher in the individualized method than in the arbitrary method (p < 0.01; ES = 5.10 [4.82; 5.37], 0.86 [0.72; 1.00] and 1.22 [1.08; 1.37], respectively). Arbitrary and individualized methods for ETL quantification based on speed zones showed similar sensitivity in depicting player locomotor demands. However, since these methods significantly differ at absolute level (based on measurement bias), arbitrary and individualized speed zones should not be used interchangeably.

scholarly journals Internal and External Training Load in Under-19 versus Professional Soccer Players during the In-Season Period

2021 ◽  
Vol 18 (2) ◽  
pp. 558
Author(s):  
Sullivan Coppalle ◽  
Guillaume Ravé ◽  
Jason Moran ◽  
Iyed Salhi ◽  
Abderraouf Ben Abderrahman ◽  
...  
Keyword(s):  
Perceived Exertion ◽  
Training Session ◽  
Training Load ◽  
Rating Of Perceived Exertion ◽  
Soccer Players ◽  
Time Intervals ◽  
Professional Soccer ◽  
Global Positioning ◽  
External Training ◽  
Soccer Team

This study aimed to compare the training load of a professional under-19 soccer team (U-19) to that of an elite adult team (EAT), from the same club, during the in-season period. Thirty-nine healthy soccer players were involved (EAT [n = 20]; U-19 [n = 19]) in the study which spanned four weeks. Training load (TL) was monitored as external TL, using a global positioning system (GPS), and internal TL, using a rating of perceived exertion (RPE). TL data were recorded after each training session. During soccer matches, players’ RPEs were recorded. The internal TL was quantified daily by means of the session rating of perceived exertion (session-RPE) using Borg’s 0–10 scale. For GPS data, the selected running speed intensities (over 0.5 s time intervals) were 12–15.9 km/h; 16–19.9 km/h; 20–24.9 km/h; >25 km/h (sprint). Distances covered between 16 and 19.9 km/h, > 20 km/h and >25 km/h were significantly higher in U-19 compared to EAT over the course of the study (p =0.023, d = 0.243, small; p = 0.016, d = 0.298, small; and p = 0.001, d = 0.564, small, respectively). EAT players performed significantly fewer sprints per week compared to U-19 players (p = 0.002, d = 0.526, small). RPE was significantly higher in U-19 compared to EAT (p =0.001, d = 0.188, trivial). The external and internal measures of TL were significantly higher in the U-19 group compared to the EAT soccer players. In conclusion, the results obtained show that the training load is greater in U19 compared to EAT.

scholarly journals Relationship between External Load and Perceptual Responses to Training in Professional Football: Effects of Quantification Method

Sports ◽  
2019 ◽  
Vol 7 (3) ◽  
pp. 68 ◽  
Author(s):  
Vincenzo Rago ◽  
João Brito ◽  
Pedro Figueiredo ◽  
Peter Krustrup ◽  
António Rebelo
Keyword(s):  
High Speed ◽  
Perceived Exertion ◽  
Training Session ◽  
Training Load ◽  
Rating Of Perceived Exertion ◽  
Quantification Method ◽  
Individual Fitness ◽  
Football Team ◽  
Maximal Aerobic Speed ◽  
Sprinting Speed

We examined the within-player correlation between external training load (ETL) and perceptual responses to training in a professional male football team (n = 13 outfield players) over an eight-week competitive period. ETL was collected using 10-Hz GPS, whereas perceptual responses were accessed through rating of perceived exertion (RPE) questionnaires. Moderate-speed running (MSR), high-speed running (HSR) and sprinting were defined using arbitrary (fixed) and individualised speed zones (based on maximal aerobic speed and maximal sprinting speed). When ETL was expressed as actual distance covered within the training session, perceptual responses were moderately correlated to MSR and HSR quantified using the arbitrary method (p < 0.05; r = 0.53 to 0.59). However, the magnitude of correlations tended to increase when the individualised method was used (p < 0.05; r = 0.58 to 0.67). Distance covered by sprinting was moderately correlated to perceptual responses only when the individualised method was used (p < 0.05; 0.55 [0.05; 0.83] and 0.53 [0.02; 0.82]). Perceptual responses were largely correlated to the sum of distance covered within all three speed running zones, irrespective of the quantification method (p < 0.05; r = 0.58 to 0.68). When ETL was expressed as percentage of total distance covered within the training session, no significant correlations were observed (p > 0.05). Perceptual responses to training load seem to be better associated with ETL, when the latter is adjusted to individual fitness capacities. Moreover, reporting ETL as actual values of distance covered within the training session instead of percentual values inform better about players’ perceptual responses to training load.

Optimal Pretaper Phase on Physical Match Performance in Professional Soccer

2020 ◽  
pp. 1-7
Author(s):  
Wassim Moalla ◽  
Mohamed Saifeddin Fessi ◽  
Sabeur Nouira ◽  
Alberto Mendez-Villanueva ◽  
Valter Di Salvo ◽  
...  
Keyword(s):  
High Intensity ◽  
High Speed ◽  
Training Load ◽  
Match Analysis ◽  
Running Performance ◽  
Low Intensity ◽  
Professional Soccer ◽  
Daily Training ◽  
Soccer Team ◽  
Analysis System

Purpose: To investigate the optimal pretaper duration on match running performance in a professional soccer team. Methods: The training load was monitored during daily training sessions and matches during 2 seasons according to different periodization strategies. Matches’ running distances were collected using match analysis system. The data were analyzed in 3 types of mesocycle blocks of 5 (M5), 4 (M4), and 3 weeks (M3), concludes all of them by 1 taper week. Results: Significant decreases in the training load during the taper weeks compared to standard weeks were observed in 3 types of mesocycle blocks (d ≥ 5; P < .01). An increase in overall match running performance was observed in matches played after the taper weeks compared to matches played after the standard weeks during M4 for all speed ranges (d ≥ 1.3; P < .05). The increase was only observed in low-intensity running (d = 1.3; P < .04) and total distance, low-intensity running, and intense running (d ≥ 1.3; P < .05) in M5 and M3, respectively. Match running performance following the taper weeks between the 3 different mesocycle durations was significantly higher in M4 for the number of high-speed running, sprinting, and high-intensity running (P < .05). The greatest enhancement of match running performance was observed at M4 when the training load was decreased by approximately 18% during the tapering period. Conclusion: This study suggests that a period of 3 standard weeks of training followed by 1 taper week is the optimal taper strategy when compared to different pretaper durations.

scholarly journals An examination of in-season external training load in semi-professional soccer players: considerations of one and two match weekly microcycles

2020 ◽  
pp. 174795412095176
Author(s):  
William E Swallow ◽  
Neil Skidmore ◽  
Richard M Page ◽  
James J Malone
Keyword(s):  
High Speed ◽  
Training Load ◽  
Electromechanical System ◽  
Soccer Players ◽  
Mems Devices ◽  
Progressive Reduction ◽  
Professional Soccer ◽  
External Training ◽  
Mean Differences ◽  
Micro Electromechanical System

The aim of the present study was to firstly, quantify the external training load (TL) of semi-professional soccer players during an annual season and secondly, to examine the influence of one (1MW) and two (2MW) match weekly microcycles. Data were collected from 24 semi-professional outfield soccer players during the 2018-2019 annual season using micro-electromechanical system (MEMS) devices for the following variables: Training duration (min), total distance (TD), Player Load (PL), high speed running (HSR) distance (5.5-7.0 m/s), and acceleration (ACC) efforts (>2 m/s2). Training sessions were defined as days before match day (i.e. MD minus), with match weeks broken down as either 1MW or 2MW. Data revealed higher TD, PL, and HSR distance on MD and MD-5 when compared to all other MD codes. MD-4 displayed significantly higher values compared to MD-1 (mean differences (M diff): TD: 785 ± 158 m; PL: 29 ± 9 au; HSR: 192 ± 63 m; ACC: 15 ± 3 #) and MD-2 (M diff: TD: 279 ± 137 m; HSR: 127 ± 54 m). During 2MW scenarios, both TD (M diff: 685 ± 328 m) and PL (M diff: 33 ± 14 au) were higher on MD-1 when compared to 1MW. However, lower values were observed for duration and HSR on MD-2 and MD-4 during 2MW compared to 1MW scenarios.These data suggest that there appears to be a progressive reduction in TD, PL, HSR and ACC leading into competitive matches based on MD- analysis. However, some variability exists in TL prescription as a result of different MW scenarios (i.e. 1MW vs. 2MW).

Within-Subject Correlation Between Salivary IgA and Measures of Training Load in Elite Football Players

2019 ◽  
Vol 14 (6) ◽  
pp. 847-849 ◽  
Author(s):  
Pedro Figueiredo ◽  
George P. Nassis ◽  
João Brito
Keyword(s):  
High Speed ◽  
Perceived Exertion ◽  
Immunoglobulin A ◽  
Correlation Coefficients ◽  
Training Load ◽  
Rating Of Perceived Exertion ◽  
Football Players ◽  
Positioning Systems ◽  
External Training ◽  
Salivary Secretory Immunoglobulin A

Purpose: To quantify the association between salivary secretory immunoglobulin A (sIgA) and training load in elite football players. Methods: Data were obtained on 4 consecutive days during the preparation camp for the Rio 2016 Olympic Games. Saliva samples of 18 elite male football players were collected prior to breakfast. The session rating of perceived exertion (s-RPE) and external training-load metrics from global positioning systems (GPS) were recorded. Within-subject correlation coefficients between training load and sIgA concentration, and magnitude of relationships, were calculated. Results: sIgA presented moderate to large negative correlations with s-RPE (r = −.39), total distance covered (r = −.55), accelerations (r = −.52), and decelerations (r = −.48). Trivial to small associations were detected between sIgA and distance covered per minute (r = .01), high-speed distance (r = −.23), and number of sprints (r = −.18). sIgA displayed a likely moderate decrease from day 1 to day 2 (d = −0.7) but increased on day 3 (d = 0.6). The training-load variables had moderate to very large rises from day 1 to day 2 (d = 0.7 to 3.2) but lowered from day 2 to day 3 (d = −5.0 to −0.4), except for distance per minute (d = 0.8) and sprints (unclear). On day 3, all training-load variables had small to large increments compared with day 1 (d = 0.4 to 1.5), except for accelerations (d = −0.8) and decelerations (unclear). Conclusions: In elite football, sIgA might be more responsive to training volume than to intensity. External load such as GPS-derived variables presented stronger association with sIgA than with s-RPE. sIgA can be used as an additional objective tool in monitoring football players.

scholarly journals Match-to-match variability in high-speed running activity in a professional soccer team

2016 ◽  
Vol 34 (24) ◽  
pp. 2215-2223 ◽  
Author(s):  
Christopher Carling ◽  
Paul Bradley ◽  
Alan McCall ◽  
Gregory Dupont
Keyword(s):  
High Speed ◽  
Professional Soccer ◽  
Running Activity ◽  
Soccer Team

Individual Response to External Training Load in Elite Football Players

2020 ◽  
Vol 15 (5) ◽  
pp. 696-704
Author(s):  
Håvard Wiig ◽  
Thor Einar Andersen ◽  
Live S. Luteberget ◽  
Matt Spencer
Keyword(s):  
External Load ◽  
High Speed ◽  
Training Load ◽  
Effect Sizes ◽  
Football Players ◽  
Individual Response ◽  
Total Distance ◽  
External Training ◽  
Tracking Devices ◽  
Very High

Purpose: To investigate within-player effect, between-player effect, and individual response of external training load from player tracking devices on session rating of perceived exertion training load (sRPE-TL) in elite football players. Methods: The authors collected sRPE-TL from 18 outfield players in 21 training sessions. Total distance, high-speed running distance (>14.4 m/s), very high-speed running distance (>19.8 m/s), PlayerLoad™, PlayerLoad2D™, and high-intensity events (HIE > 1.5, HIE > 2.5, and HIE > 3.5 m/s) were extracted from the tracking devices. The authors modeled within-player and between-player effects of single external load variables on sRPE-TL, and multiple levels of variability, using a linear mixed model. The effect of 2 SDs of external load on sRPE-TL was evaluated with magnitude-based inferences. Results: Total distance, PlayerLoad™, PlayerLoad2D™, and HIE > 1.5 had most likely substantial within-player effects on sRPE-TL (100%–106%, very large effect sizes). Moreover, the authors observed likely substantial between-player effects (12%–19%, small to moderate effect sizes) from the majority of the external load variables and likely to very likely substantial individual responses of PlayerLoad™, high-speed running distance, very high-speed running distance, and HIE > 1.5 (19%–30% coefficient of variation, moderate to large effect sizes). Finally, sRPE-TL showed large to very large between-session variability with all external load variables. Conclusions: External load variables with low intensity-thresholds had the strongest relationship with sRPE-TL. Furthermore, the between-player effect of external load and the individual response to external load advocate for monitoring sRPE-TL in addition to external load. Finally, the large between-session variability in sRPE-TL demonstrates that substantial amounts of sRPE-TL in training sessions are not explained by single external load variables.

scholarly journals The Integration of Internal and External Training Load Metrics in Hurling

2016 ◽  
Vol 53 (1) ◽  
pp. 211-221 ◽  
Author(s):  
Shane Malone ◽  
Dominic Doran ◽  
Ibrahim Akubat ◽  
Kieran Collins
Keyword(s):  
Blood Lactate ◽  
Aerobic Fitness ◽  
High Speed ◽  
Pearson Correlation ◽  
Training Load ◽  
Significant Relationships ◽  
Treadmill Testing ◽  
External Training ◽  
Fitness Measures ◽  
Training Impulse

AbstractThe current study aimed to assess the relationship between the hurling player’s fitness profile and integrated training load (TL) metrics. Twenty-five hurling players performed treadmill testing for VO2max, the speed at blood lactate concentrations of 2 mmol•L-1 (vLT) and 4 mmol•L-1 (vOBLA) and the heart rate-blood lactate profile for calculation of individual training impulse (iTRIMP). The total distance (TD; m), high speed distance (HSD; m) and sprint distance (SD; m) covered were measured using GPS technology (4-Hz, VX Sport, Lower Hutt, New Zealand) which allowed for the measurement of the external TL. The external TL was divided by the internal TL to form integration ratios. Pearson correlation analyses allowed for the assessment of the relationships between fitness measures and the ratios to performance during simulated match play. External measures of the TL alone showed limited correlations with fitness measures. Integrated TL ratios showed significant relationships with fitness measures in players. TD:iTRIMP was correlated with aerobic fitness measures VO2max (r = 0.524; p = 0.006; 95% CI: 0.224 to 0.754; large) and vOBLA (r = 0.559; p = 0.003; 95% CI: 0.254 to 0.854; large). HSD:iTRIMP also correlated with aerobic markers for fitness vLT (r = 0.502; p = 0.009; 95% CI: 0.204 to 0.801; large); vOBLA (r = 0.407; p = 0.039; 95% CI: 0.024 to 0.644; moderate). Interestingly SD:iTRIMP also showed significant correlations with vLT (r = 0.611; p = 0.001; 95% CI: 0.324 to 0.754; large). The current study showed that TL ratios can provide practitioners with a measure of fitness as external performance alone showed limited relationships with aerobic fitness measures.

scholarly journals In-season internal and external training load quantification of an elite European soccer team

2018 ◽  
Author(s):  
Rafael Soares Oliveira ◽  
João Paulo Brito ◽  
Alexandre Martins ◽  
Bruno Mendes ◽  
Francisco Calvete ◽  
...  
Keyword(s):  
High Speed ◽  
Perceived Exertion ◽  
Training Load ◽  
Rating Of Perceived Exertion ◽  
Soccer Players ◽  
Soccer Teams ◽  
External Training ◽  
Daily Training ◽  
Player Positions ◽  
Level Of Effort

Elite soccer teams that participate in European competitions often have a difficult schedule, involving weeks in which they play up to three matches, which leads to acute and transient subjective, biochemical, metabolic and physical disturbances in players over the subsequent hours and days. Inadequate time recovery between matches can expose players to the risk of training and competing whilst not fully recovered. Controlling the level of effort and fatigue of players to reach higher performances during the matches is therefore critical. Therefore, the aim of the current study was to provide the first report of seasonal internal and external training load (TL) that included Hooper Index (HI) scores in elite soccer players during an in-season period. Sixteen elite soccer players were sampled, using global position system, session rating of perceived exertion (s-RPE) and HI scores during the daily training sessions throughout the 2015-2016 in-season period. Data were analysed across ten mesocycles (M: 1 to 10) and collected according to the number of days prior to a match. Total daily distance covered was higher at the start (M1 and M3) compared to the final mesocycle (M10) of the season. M1 (5589m) reached a greater distance than M5 (4473m) (ES = 9.33 [12.70, 5.95]) and M10 (4545m) (ES = 9.84 [13.39, 6.29]). M3 (5691m) reached a greater distance than M5 (ES = 9.07 [12.36, 5.78]), M7 (ES = 6.13 [8.48, 3.79]) and M10 (ES = 9.37 [12.76, 5.98]). High-speed running distance was greater in M1 (227m), than M5 (92m) (ES = 27.95 [37.68, 18.22]) and M10 (138m) (ES = 8.46 [11.55, 5.37]). Interestingly, the s-RPE response was higher in M1 (331au) in comparison to the last mesocycle (M10, 239au). HI showed minor variations across mesocycles and in days prior to the match. Every day prior to a match, all internal and external TL variables expressed significant lower values to other days prior to a match (p<0.01). In general, there were no differences between player positions. Conclusions: Our results reveal that despite the existence of some significant differences between mesocycles, there were minor changes across the in-season period for the internal and external TL variables used. Furthermore, it was observed that MD-1 presented a reduction of external TL (regardless of mesocycle) while internal TL variables did not have the same record during in-season match-day-minus.

scholarly journals Relationship Between Internal and External Training Load in Field Hockey

2020 ◽  
Vol 1 (1) ◽  
Author(s):  
Katrine Tuft ◽  
Mykolas Kavaliauskas
Keyword(s):  
High Power ◽  
High Speed ◽  
Power Distance ◽  
Training Load ◽  
Field Hockey ◽  
Total Distance ◽  
Perceived Wellness ◽  
External Training ◽  
High Power Distance ◽  
Training Efficiency

Training load monitoring in team sports is important in order to plan and evaluate training strategies and ensure optimal performance. Integration of internal and external training load measures into a single training efficiency metric reduces the effect of confounding variables on training loads. The purpose of this study was to generate a training efficiency metric to evaluate in-season field hockey training. Further, the relationship between players’ perceived wellness the training efficiency metric was determined. Internal (training impulse and session rating of perceived exertion; TRIMP and sRPE) and external (total distance, high-speed distance, acceleration load, high-power distance, metabolic work, mechanical work, and impulse) training load was collected over a 6-week period for 11 male national level field hockey players (21.1 ± 1.2 years, 178.7 ± 8.6 cm, 4.6 ± 6.3 kg). The relationships between internal and external training load were assessed, and two training efficiency models were generated through mixed model analyses using sRPE and TRIMP. Subsequently, the relationships between training efficiency and perceived wellness were examined. The statistical analyses determined that total distance, high-speed distance, high-power distance, and metabolic work (r = 0.311-0.573) were included in the TRIMP training efficiency model. The sRPE training efficiency model included total distance, high-speed distance, high-power distance, metabolic work, and mechanical work (r = 0.329-0.757). Moreover, neither of the training efficiency models were related to daily cumulative wellness scores (TRIMP: r = -0.046; p = 0.336; sRPE: r = -0.034; p = 0.370). The study showed that the sRPE training efficiency model provided a better reflection of in-season field hockey training demands than the TRIMP model. Additionally, practitioners are not advised to adjust training based on acute changes in players’ perceived wellness.

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